Abstract: A learned image compression system increases compression efficiency by using a novel conditional context model with embedded autoregressive neighbors and hyperpriors, which can accurately estimate the entropy rate for rate distortion optimization. Generalized Divisive Normalization (GDN) in Residual Neural Network is used in the encoder and decoder networks for fast convergence rate and efficient feature representation.

Abstract: Embodiments of the present invention disclose a method and an apparatus for detecting frame types. The method includes: detecting play time of each frame; and if the play time of a current frame is less than the maximum play time of received frames, determining the current frame as a bi-directional predicted frame, B-frame. In the technical solutions provided by the embodiments of the present invention, the frame types are determined according to a coding sequence of various frames and comparison between data amounts of various frames received earlier and later, without decoding a payload. Therefore the impact of a reduction factor is eliminated and the frame types can be detected more accurately.

Abstract: Embodiments of the present invention disclose a method and an apparatus for detecting frame types. The method includes: detecting play time of each frame; and if the play time of a current frame is less than the maximum play time of received frames, determining the current frame as a bi-directional predicted frame, B-frame. In the technical solutions provided by the embodiments of the present invention, the frame types are determined according to a coding sequence of various frames and comparison between data amounts of various frames received earlier and later, without decoding a payload. Therefore the impact of a reduction factor is eliminated and the frame types can be detected more accurately.